FDG PET/CT Assesses the Risk of Femoral Pathological Fractures in Patients With Metastatic Breast Cancer

Abstract

Purpose Assessment of pathological fracture risk is critical to optimize the use of prophylactic orthopedic fixation to prevent pathological fractures. Better prediction of pathological fracture risk is needed. We evaluated if quantitative measures of FDG-avidity can assess femoral pathological fracture risk in patients with metastatic breast cancer (MBC). Methods A HIPAA-compliant retrospective case-control study was performed under IRB waiver. Patients with MBC who received an FDG PET/CT from 1/2008–12/2014 and had pathological fracture of the proximal femur within three months of PET/CT were selected as cases. Patients with MBC who had an FDG PET/CT in 2013 were sequentially screened in reverse chronological order to identify patients with proximal femoral metastases on PET/CT but no subsequent pathological fracture to serve as a control group. The pre-specified goal was to have twice the number of controls as cases. Target lesions in the proximal femur, from femoral head to 5 cm below the lesser trochanter, were analyzed on FDG PET/CT for SUVmax, SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG). Wilcoxon rank-sum test was used to compare continuous variables in cases and controls. A nonparametric receiver operating characteristic (ROC) analysis was performed to assess the ability of quantitative FDG measurements to differentiate between cases and controls. Results In 27 cases with pathological fracture and 55 controls without pathological fracture, all four quantitative measures of FDG-avidity were statistically different between cases and controls (p <.001). A TLG of 81 could differentiate between fracture and non-fracture patients with accuracy, sensitivity, and specificity of 0.83, 0.85, and 0.80, respectively. Conclusion Quantitative measures of FDG avidity may help identify breast cancer patients at high risk of subsequent pathological fracture of the proximal femur.

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“…van der Linden et al advise to use 3-cm cortical involvement as a cutoff point [5,27]. The most promising are CT-based algorithms that are currently being developed [25]. Once such models will be able to provide quick predictions in the clinical setting, hopefully the everlasting question of how to determine the fracture risk will belong to the past.…”

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